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English CM, Kitzhaber ZB, Sanim KRI, Vitzilaios N, Hodgson ME, Richardson TL, Myrick ML. Filter Fluorometer Calibration Without the Fluorometer. APPLIED SPECTROSCOPY 2023; 77:1053-1063. [PMID: 37350765 DOI: 10.1177/00037028231181593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/24/2023]
Abstract
We recently described a lightweight, low-power, waterproof filter fluorometer using a 180° backscatter geometry for chlorophyll-a (chl-a) detection. Before it was constructed it was modeled to ensure it would have satisfactory performance. This manuscript repeats the modeling process that allows the calibration slope and detection limit for a fluorescent analyte in water to be estimated from system component performance and conventional spectrofluorometry alone. These values are validated by comparison to the experimental result of calibration from the completed instrument. Our model yields a calibration slope of 8.22 mV-L/µg for dissolved chl-a, consistent with the experimentally measured slope of 8.21 mV-L/µg. The detection limit modeled from this slope and an estimate of the baseline noise of the instrument was 0.15 µg/L chl-a, while the measured detection limit using real blank samples was 0.18 µg/L, in 0.1 s differential measurements.
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Affiliation(s)
- Caitlyn M English
- Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Zechariah B Kitzhaber
- Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Kazi Ragib I Sanim
- Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA
| | - Nikolaos Vitzilaios
- Department of Mechanical Engineering, University of South Carolina, Columbia, SC, USA
| | - Michael E Hodgson
- Department of Geography, University of South Carolina, Columbia, SC, USA
| | - Tammi L Richardson
- Department of Biological Sciences, University of South Carolina, Columbia, SC, USA
| | - Michael L Myrick
- Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
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English CM, Kitzhaber ZB, Sanim KRI, Kalaitzakis M, Kosaraju B, Pinckney JL, Hodgson ME, Vitzilaios NI, Richardson TL, Myrick ML. Chlorophyll Fluorometer for Intelligent Water Sampling by a Small Uncrewed Aircraft System (sUAS). APPLIED SPECTROSCOPY 2023; 77:94-105. [PMID: 36065908 DOI: 10.1177/00037028221126748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
We describe a waterproof, lightweight (1.3 kg), low-power (∼1.1 W average power) fluorometer operating on 5 V direct current deployed on a small uncrewed aircraft system (sUAS) to measure chlorophyll and used for triggering environmental water sampling by the sUAS. The fluorometer uses a 450 nm laser modulated at 10 Hz for excitation and a standard photodiode and transimpedance amplifier for the detection of fluorescence. Additional detectors are available for measuring laser intensity and light scattering. Control of the fluorometer and communication between the fluorometer and the Raspberry Pi 4B computer controlling the sampler were provided by an Arduino microcontroller using the robot operating system (ROS). Calibrations were based on standards of dissolved chlorophyll extracted from Chlorella powder (a widely available dietary supplement). The detection limit for chlorophyll from these calibrations was found to be 0.2 μg per liter of water for a single 0.1 s differential measurement. The detection limit decreases with the square root of the integration time as expected. Detection limits increase by a factor of two to three when mounted in the sUAS due to electrical noise; sUAS acoustic noise and vibration do not appear to contribute significantly.
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Affiliation(s)
- Caitlyn M English
- Department of Chemistry and Biochemistry, 2629University of South Carolina, Columbia, SC, USA
| | - Zechariah B Kitzhaber
- Department of Chemistry and Biochemistry, 2629University of South Carolina, Columbia, SC, USA
| | - Kazi Ragib I Sanim
- Department of Mechanical Engineering, 2629University of South Carolina, Columbia, SC, USA
| | - Michail Kalaitzakis
- Department of Mechanical Engineering, 2629University of South Carolina, Columbia, SC, USA
| | - Bhanuprakash Kosaraju
- Department of Mechanical Engineering, 2629University of South Carolina, Columbia, SC, USA
| | - James L Pinckney
- Department of Biological Sciences, 2629University of South Carolina, Columbia, SC, USA
| | - Michael E Hodgson
- Department of Geography, 2629University of South Carolina, Columbia, SC, USA
| | - Nikolaos I Vitzilaios
- Department of Mechanical Engineering, 2629University of South Carolina, Columbia, SC, USA
| | - Tammi L Richardson
- Department of Biological Sciences, 2629University of South Carolina, Columbia, SC, USA
| | - Michael L Myrick
- Department of Chemistry and Biochemistry, 2629University of South Carolina, Columbia, SC, USA
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Machine Learning Powered Microalgae Classification by Use of Polarized Light Scattering Data. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12073422] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Microalgae are widely distributed in the ocean, which greatly affects the ocean environment. In this work, a dataset is presented, including the polarized light scattering data of 35 categories of marine microalgae. To analyze the dataset, several machine learning algorithms are applied and compared, such as linear discrimination analysis (LDA) and two types of support vector machine (SVM). Results show that non-linear SVM performs the best among these algorithms. Then, two data preparation approaches for non-linear SVM are compared. Subsequently, more than 10 categories of microalgae out of the dataset can be identified with an accuracy greater than 0.80. The basis of the dataset is shown by finding the categories independent to each other. The discussions about the performance of different incident polarization of light gives some clues to design the optimal incident polarization of light for future instrumentation. With this proposed technique and the dataset, these microalgae can be well differentiated by polarized light scattering data.
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Faulkner ST, Rekully CM, Lachenmyer EM, Kara E, Richardson TL, Shaw TJ, Myrick ML. Single-Cell and Bulk Fluorescence Excitation Signatures of Seven Phytoplankton Species During Nitrogen Depletion and Resupply. APPLIED SPECTROSCOPY 2019; 73:304-312. [PMID: 30345799 DOI: 10.1177/0003702818812090] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Phytoplankton play a vital role as primary producers in aquatic ecosystems. One common approach to classifying phytoplankton is fluorescence excitation spectroscopy, which leverages the variation in types and concentrations of pigments among different phytoplankton taxonomic groups. Here, we used a fluorescence imaging photometer to measure excitation ratios ("signatures") of single cells and bulk cultures of seven differently pigmented phytoplankton species as they progressed from nitrogen N-replete to N-depleted conditions. Our objective was to determine whether N depletion alters the fluorescence excitation signature of each species and, if so, how quickly they recover when N (as nitrate) was resupplied, because these factors affect our ability to classify the species correctly. Of the seven species studied, only Proteomonas sulcata, a marine cryptophyte, showed measurable changes in single-cell fluorescence excitation ratios and bulk fluorescence excitation spectra. These changes were likely due to decreases in the cellular concentration of phycoerythrin, a N-rich pigment, as N became scarce. Within 3 h of resupply of N, fluorescence signatures began returning to pre-depletion values and were indistinguishable from N-replete cells by 80 h after resupply. These data suggest that our classification approach is robust for non-PE containing phytoplankton. PE-containing phytoplankton might exhibit systematic changes in their signatures depending on their level of N depletion, but this could be detected and the phytoplankton re-classified following a few hours of incubation in N replete conditions.
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Affiliation(s)
- Stefan T Faulkner
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Cameron M Rekully
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Eric M Lachenmyer
- 2 School of the Earth, Ocean, and Environment, University of South Carolina, Columbia, SC, USA
| | - Ergun Kara
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Tammi L Richardson
- 2 School of the Earth, Ocean, and Environment, University of South Carolina, Columbia, SC, USA
- 3 Department of Biological Sciences, University of South Carolina, Columbia, SC, USA
| | - Timothy J Shaw
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Michael L Myrick
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
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Rekully CM, Faulkner ST, Kara E, Richardson TL, Shaw TJ, Myrick ML. Asymmetric Versus Symmetric Filter Wheels and Associated Processing Algorithms: Results from Asynchronous Fluorescence Imaging Photometer Measurements of Phytoplankton. APPLIED SPECTROSCOPY 2019; 73:104-114. [PMID: 30012006 DOI: 10.1177/0003702818792285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The use of rotating filter wheels is common in photometric applications. Traditional filter wheel designs typically exhibit a number of filter openings spaced evenly about the circumference of the wheel. In this work we examine a number of shortcomings of this traditional filter design in measurements of phytoplankton fluorescence made with our fluorescence imaging photometer (FIP). We present an alternative asymmetric wheel design that offers a number of advantages over the traditional design as well as a new processing algorithm designed to accommodate convolution of signals from adjacent channels inherent in measurements collected with the asymmetric design. This approach eliminates the need for a separate signal to establish timing and wheel position, unambiguously establishes filter order even when the direction of rotation is unknown, allows for better estimates of signal baseline, and is more resilient to effects of vibration and other dynamic processes that could occur on the time scale of wheel rotation. We demonstrate performance improvements for phytoplankton fluorescence measurements associated with the new wheel design and algorithm compared with previously published methods using the FIP. Both the improved image processing algorithm and filter wheel design were found to reduce noise in our measurements significantly.
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Affiliation(s)
- Cameron M Rekully
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Stefan T Faulkner
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Ergun Kara
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - Tammi L Richardson
- 2 Department of Biological Sciences, University of South Carolina, Columbia, SC, USA
| | - Timothy J Shaw
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
| | - M L Myrick
- 1 Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA
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